| --- |
| language: |
| - en |
| license: other |
| task_categories: |
| - text-classification |
| - conversational |
| task_ids: |
| - intent-classification |
| - sentiment-classification |
| tags: |
| - ecommerce |
| - customer-service |
| - synthetic |
| - intent |
| - sentiment |
| - chatbot |
| - dialogue |
| - jsonl |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # EcommerceAI Dataset — English E-commerce Customer Service |
|
|
| ## Dataset Description |
|
|
| A high-quality **synthetic** English-language dataset of e-commerce |
| customer service conversations with full intent and sentiment annotations. |
|
|
| > ⚠️ **Transparency Notice:** This is a synthetic dataset. All conversations |
| > are programmatically generated. No real customer data is included. |
| > Every record is labeled `"data_type": "SYNTHETIC"` in metadata. |
| |
| --- |
| |
| ## Dataset Stats |
| |
| | Metric | Value | |
| |--------|-------| |
| | Conversations | 5,000 | |
| | Dialogue Turns | 47,028 | |
| | Avg Turns/Conversation | 9.4 | |
| | Language | English | |
| | Issue Categories | 5 | |
| | Product Categories | 10 | |
| | Intent Classes | 12 | |
| |
| --- |
| |
| ## Issue Categories |
| |
| | Category | Count | |
| |----------|-------| |
| | Late Delivery | 1,000 | |
| | Wrong Item Received | 1,000 | |
| | Refund Request | 1,000 | |
| | Damaged Item | 1,000 | |
| | Product Inquiry | 1,000 | |
| |
| --- |
| |
| ## Data Schema |
| |
| ```json |
| { |
| "id": "uuid-v4", |
| "metadata": { |
| "domain": "ecommerce_customer_service", |
| "issue_type": "late_delivery", |
| "product_category": "electronics", |
| "language": "en", |
| "data_type": "SYNTHETIC", |
| "quality_tier": "enterprise", |
| "turns_count": 10 |
| }, |
| "conversation": [ |
| { |
| "role": "user", |
| "content": "My order hasn't arrived in 7 days.", |
| "intent": "late_delivery", |
| "sentiment": "negative" |
| }, |
| { |
| "role": "agent", |
| "content": "I'm sorry to hear that. Let me check your order.", |
| "intent": "acknowledge", |
| "sentiment": "positive" |
| } |
| ] |
| } |
| ``` |
| |
| --- |
|
|
| ## Quick Load |
|
|
| ```python |
| # Option 1 — HuggingFace Datasets |
| from datasets import load_dataset |
| ds = load_dataset("YOUR_USERNAME/ecommerce-cs-dataset") |
| |
| # Option 2 — Pure Python |
| import json |
| conversations = [] |
| with open('ecommerce_cs_en_synthetic.jsonl') as f: |
| for line in f: |
| conversations.append(json.loads(line)) |
| |
| # Filter by issue type |
| refunds = [c for c in conversations |
| if c['metadata']['issue_type'] == 'refund_request'] |
| ``` |
|
|
| --- |
|
|
| ## Use Cases |
|
|
| - ✅ Fine-tuning LLMs for customer service chatbots |
| - ✅ Training intent classifiers (12 classes) |
| - ✅ Training sentiment analysis models |
| - ✅ Dialogue state tracking research |
| - ✅ Augmenting real-world datasets |
| - ✅ Testing chatbot pipelines |
|
|
| --- |
|
|
| ## 🔒 Full Dataset (Commercial License) |
|
|
| This repository contains a **free sample of 500 conversations.** |
|
|
| The full dataset **(5,000 conversations, 47K+ turns)** with commercial |
| license is available here: |
|
|
| 👉 **[Get Full Dataset on Sellix → YOUR_SELLIX_LINK]** |
|
|
| Includes: |
| - Full 5,000 conversation JSONL |
| - Complete JSON array format |
| - Data card & documentation |
| - Commercial use license |
|
|
| --- |
|
|
| ## License |
|
|
| Sample (this repo): CC BY-NC 4.0 — free for research & personal use. |
| Full dataset: Commercial license — see Sellix listing for terms. |
|
|
| --- |
|
|
| ## Citation |
|
|
| If you use this dataset in research, please cite: |
|
|
